A wide variety of applications allow a user to query and display report data, where the report data may be culled from multiple, sometimes disparate data sources. For example, if a user, through the use of a report generation tool, is interested in data such that the data is dependent upon both transactional and analytics data, a query to produce the data may be exceedingly slow because the necessary data is spread across multiple data stores and because the data stores may include massive amounts of data. In such a circumstance, if a user requests to see keywords for which more than 50 cents was bid on in the past week, and further where those keywords received at least 1000 clicks, the query necessary to satisfy such a request would be time and computationally intensive. However, it is often the case where a user is interested in data for certain, commonly requested time frames such as the previous week, or the previous two weeks, or the quarter to date, among other frequently specified date ranges. A further impediment to quickly satisfying a query that depends on both transactional and analytics data is that the structure of the stored data has different characteristics.